Adoptive transfer of T cells is a promising clinical cancer therapy that relies on enhancing the adaptive immune response to target tumor cells in vivo. Widespread application of this therapy, however, has been hindered by the necessary expansion of large populations of T cells for each patient (often selected for tumor antigen specificity) and loss of functionality of the T cells post-transfer. Our long-term objective is to understand how T cell activation is dampened in vivo by the tumor milieu and to be able to evaluate the responsiveness ex vivo-expanded T cells accurately for cancer therapy. Microfluidic chips are ideal for high-throughput parallel experimentation and automation. In addition, microfluidics also provides the relevant length scales (~microns) and unique physical phenomena (e.g. laminar flow) to handle cells. The type of multiplex data that we can obtain from this technology will enable quantitative modeling of T cell activation and better understanding and characterization of anergy. The objective of this R21 project is to engineer a multiplex microfluidic assay to quantify T cell activation on a small population of cells with high temporal resolution. The hypothesis is that capturing the early dynamics of T cell activation of ex vivo expanded clones would improve upon current measures of T cell functionality. The first component of this project is to develop the high-throughput microfluidic system for multiple time-point stimulation and lysis of cells;in parallel, we are to develop biochemical assays to characterize the performance of the system and the cell state. The second component is to perform in vitro characterization of ex vivo expanded T cells for distinguishing anergic versus responsive behavior. The approach is innovative because the technology developed here dramatically increases the capabilities and throughput of existing assays in evaluating T cells for adoptive transfer. Furthermore, this work proposes and tests a new paradigm in T cell evaluation using multiplex quantitative means. The proposed research is significant because it is expected to expand the toolbox of cancer therapy and possibly other related quantitative biosciences and medical technologies.